The present invention relates to medical imaging of the heart, and more particularly, to automatic detection of native and bypass coronary ostia in cardiac computed tomography (CT) volumes.
According to statistics from the United States Center for Disease Control and Prevention, cardiovascular disease (CVD) is the leading cause of death in the United States. Coronary artery disease (CAD) is among the most common types of CVD. CAD is often caused by the narrowing of the coronary artery (or atherosclerosis), which lead to coronary artery stenosis and can cause heart attack, angina, or both. Coronary artery bypass surgery is a well established surgical procedure to improve the blood supply to the coronary circulation supplying the myocardium when coronary artery stenosis is too severe and medical therapy does not help. In coronary artery bypass surgery, arteries or veins from elsewhere in the patient's body are grafted to the coronary arteries to bypass atherosclerotic narrowings. Typically, one end of the graft is sewn onto to a coronary artery beyond the blockages and the other is attached to the ascending aorta. Alternatively, the distal end of the left internal thoracic artery (LITA) can be attached to the coronary artery with its proximal end connected to the subclavian artery.
Many techniques have been developed for imaging the heart to diagnose CAD, including computed tomography (CT), magnetic resonance imaging (MRI), fluoroscopic angiography, etc. Compared to MRI, CT provides superior space resolution (especially between image slices) and high temporary resolution. Using recently developed technology for CT scanning, it is possible to scan the entire heart in one heart beat, thus minimizing motion artifacts. Compared to fluoroscopic angiography, CT is a non-invasive imaging technique, and therefore reduces the risk and complications associated with the minimal surgery associated with fluoroscopic angiography. In order to facilitate diagnosis of CAD, it is desirable to develop a system that can efficiently and effectively extract the coronary artery centerlines from a cardiac CT volume. Using the extracted coronary artery centerlines, a curved multi-planar reformation (curved MPR) image can be generated to give a physician an overview of the entire coronary artery. Lumen segmentation can further provide quantification of coronary stenosis.
Many coronary artery centerline extraction algorithms utilize a vessel tracing method to trace an artery, starting from the aortic root. The coronary ostia are often used to initialize such vessel tracing methods. Although earlier methods required a user to specify the coronary ostia in order to initialize the tracing method, various automatic seeding methods have been proposed to initiate the coronary artery centerline extraction. For example, various automatic or semiautomatic coronary ostia detection methods have been proposed. Conventional methods for detecting the coronary ostia typically need to segment the aorta before detecting the coronary ostia. Such conventional methods are not robust under imaging artifacts and severe obstruction of the coronary around the ostia. Furthermore, conventional coronary ostia detection methods typically perform poorly for detecting bypass coronary ostia.